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Gotowe bibliografie tematyczne / BINARIZATION TECHNIQUE

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Artykuły w czasopismach

Gotowa bibliografia na temat „BINARIZATION TECHNIQUE”

Autor: Grafiati

Data publikacji: 11 września 2023

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Artykuły w czasopismach na temat "BINARIZATION TECHNIQUE"

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Thepade, Sudeep, Rik Das, and Saurav Ghosh. "A Novel Feature Extraction Technique Using Binarization of Bit Planes for Content Based Image Classification." Journal of Engineering 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/439218.

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A number of techniques have been proposed earlier for feature extraction using image binarization. Efficiency of the techniques was dependent on proper threshold selection for the binarization method. In this paper, a new feature extraction technique using image binarization has been proposed. The technique has binarized the significant bit planes of an image by selecting local thresholds. The proposed algorithm has been tested on a public dataset and has been compared with existing widely used techniques using binarization for extraction of features. It has been inferred that the proposed met

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Yu, Young-Jung. "Document Image Binarization Technique using MSER." Journal of the Korea Institute of Information and Communication Engineering 18, no. 8 (2014): 1941–47. http://dx.doi.org/10.6109/jkiice.2014.18.8.1941.

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MAKRIDIS, MICHAEL, and N. PAPAMARKOS. "AN ADAPTIVE LAYER-BASED LOCAL BINARIZATION TECHNIQUE FOR DEGRADED DOCUMENTS." International Journal of Pattern Recognition and Artificial Intelligence 24, no. 02 (2010): 245–79. http://dx.doi.org/10.1142/s0218001410007889.

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This paper presents a new technique for adaptive binarization of degraded document images. The proposed technique focuses on degraded documents with various background patterns and noise. It involves a preprocessing local background estimation stage, which detects for each pixel that is considered as background one, a proper grayscale value. Then, the estimated background is used to produce a new enhanced image having uniform background layers and increased local contrast. That is, the new image is a combination of background and foreground layers. Foreground and background layers are then sep

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CHI, ZHERU, and QING WANG. "DOCUMENT IMAGE BINARIZATION WITH FEEDBACK FOR IMPROVING CHARACTER SEGMENTATION." International Journal of Image and Graphics 05, no. 02 (2005): 281–309. http://dx.doi.org/10.1142/s0219467805001768.

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Binarization of gray scale document images is one of the most important steps in automatic document image processing. In this paper, we present a two-stage document image binarization approach, which includes a top-down region-based binarization at the first stage and a neural network based binarization technique for the problematic blocks at the second stage after a feedback checking. Our two-stage approach is particularly effective for binarizing text images of highlighted or marked text. The region-based binarization method is fast and suitable for processing large document images. However,

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Pagare, Mr Aniket. "Document Image Binarization using Image Segmentation Technique." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (2021): 1173–76. http://dx.doi.org/10.22214/ijraset.2021.36597.

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Segmentation of text from badly degraded document images is an extremely difficult assignment because of the high inter/Intra variety between the record foundation and the frontal area text of various report pictures. Picture preparing and design acknowledgment algorithms set aside more effort for execution on a solitary center processor. Designs Preparing Unit (GPU) is more mainstream these days because of its speed, programmability, minimal expense and more inbuilt execution centers in it. The primary objective of this exploration work is to make binarization quicker for acknowledgment of a

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Abbood, Alaa Ahmed, Mohammed Sabbih Hamoud Al-Tamimi, Sabine U. Peters, and Ghazali Sulong. "New Combined Technique for Fingerprint Image Enhancement." Modern Applied Science 11, no. 1 (2016): 222. http://dx.doi.org/10.5539/mas.v11n1p222.

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This paper presents a combination of enhancement techniques for fingerprint images affected by different type of noise. These techniques were applied to improve image quality and come up with an acceptable image contrast. The proposed method included five different enhancement techniques: Normalization, Histogram Equalization, Binarization, Skeletonization and Fusion. The Normalization process standardized the pixel intensity which facilitated the processing of subsequent image enhancement stages. Subsequently, the Histogram Equalization technique increased the contrast of the images. Furtherm

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Adhari, Firman Maulana, Taufik Fuadi Abidin, and Ridha Ferdhiana. "License Plate Character Recognition using Convolutional Neural Network." Journal of Information Systems Engineering and Business Intelligence 8, no. 1 (2022): 51–60. http://dx.doi.org/10.20473/jisebi.8.1.51-60.

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Background: In the last decade, the number of registered vehicles has grown exponentially. With more vehicles on the road, traffic jams, accidents, and violations also increase. A license plate plays a key role in solving such problems because it stores a vehicle’s historical information. Therefore, automated license-plate character recognition is needed. Objective: This study proposes a recognition system that uses convolutional neural network (CNN) architectures to recognize characters from a license plate’s images. We called it a modified LeNet-5 architecture. Methods: We used four differen

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García, José, Paola Moraga, Matias Valenzuela, et al. "A Db-Scan Binarization Algorithm Applied to Matrix Covering Problems." Computational Intelligence and Neuroscience 2019 (September 16, 2019): 1–16. http://dx.doi.org/10.1155/2019/3238574.

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The integration of machine learning techniques and metaheuristic algorithms is an area of interest due to the great potential for applications. In particular, using these hybrid techniques to solve combinatorial optimization problems (COPs) to improve the quality of the solutions and convergence times is of great interest in operations research. In this article, the db-scan unsupervised learning technique is explored with the goal of using it in the binarization process of continuous swarm intelligence metaheuristic algorithms. The contribution of the db-scan operator to the binarization proce

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Rozen, Tal, Moshe Kimhi, Brian Chmiel, Avi Mendelson, and Chaim Baskin. "Bimodal-Distributed Binarized Neural Networks." Mathematics 10, no. 21 (2022): 4107. http://dx.doi.org/10.3390/math10214107.

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Binary neural networks (BNNs) are an extremely promising method for reducing deep neural networks’ complexity and power consumption significantly. Binarization techniques, however, suffer from ineligible performance degradation compared to their full-precision counterparts. Prior work mainly focused on strategies for sign function approximation during the forward and backward phases to reduce the quantization error during the binarization process. In this work, we propose a bimodal-distributed binarization method (BD-BNN). The newly proposed technique aims to impose a bimodal distribution of t

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Joseph, Manju, and Jijina K. P. Jijina K.P. "Simple and Efficient Document Image Binarization Technique For Degraded Document Images." International Journal of Scientific Research 3, no. 5 (2012): 217–20. http://dx.doi.org/10.15373/22778179/may2014/65.

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